CME 102: Ordinary Differential Equations for Engineers (ENGR 155A)
Analytical and numerical methods for solving ordinary differential equations arising in engineering applications: Solution of initial and boundary value problems, series solutions, Laplace transforms, and nonlinear equations; numerical methods for solving ordinary differential equations, accuracy of numerical methods, linear stability theory, finite differences. Introduction to MATLAB programming as a basic tool kit for computations. Problems from various engineering fields. Prerequisite: 10 units of AP credit (Calc BC with 4 or 5, or Calc AB with 5), or
Math 41 and 42. Recommended:
CME100.
Terms: Aut, Win, Spr, Sum

Units: 5

UG Reqs: GER:DBMath, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Darve, E. (PI)
;
Le, H. (PI)
;
Baalbaki, W. (TA)
;
DePaul, G. (TA)
;
Gnanasekaran, A. (TA)
;
Lorenzetti, J. (TA)
;
Martinez, J. (TA)
;
Moon, T. (TA)
;
Najmabadi, C. (TA)
;
Sanchez, S. (TA)
;
Simpson, C. (TA)
;
Suresh, S. (TA)
;
Westhoff, P. (TA)
CME 106: Introduction to Probability and Statistics for Engineers (ENGR 155C)
Probability: random variables, independence, and conditional probability; discrete and continuous distributions, moments, distributions of several random variables. Topics in mathematical statistics: random sampling, point estimation, confidence intervals, hypothesis testing, nonparametric tests, regression and correlation analyses; applications in engineering, industrial manufacturing, medicine, biology, and other fields. Prerequisite:
CME 100/ENGR154 or
MATH 51 or 52.
Terms: Win, Sum

Units: 4

UG Reqs: GER:DBMath, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Khayms, V. (PI)
;
An, J. (TA)
;
Ayoul, T. (TA)
;
FournierBidoz, E. (TA)
;
Gao, P. (TA)
;
Genin, M. (TA)
;
Krason, M. (TA)
;
Lakshman, V. (TA)
;
Slottje, A. (TA)
CME 108: Introduction to Scientific Computing (MATH 114)
Introduction to Scientific Computing Numerical computation for mathematical, computational, physical sciences and engineering: error analysis, floatingpoint arithmetic, nonlinear equations, numerical solution of systems of algebraic equations, banded matrices, least squares, unconstrained optimization, polynomial interpolation, numerical differentiation and integration, numerical solution of ordinary differential equations, truncation error, numerical stability for time dependent problems and stiffness. Implementation of numerical methods in MATLAB programming assignments. Prerequisites:
MATH 51, 52, 53; prior programming experience (MATLAB or other language at level of
CS 106A or higher).
Terms: Sum

Units: 3

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Le, H. (PI)
;
Ying, L. (PI)
;
Aboumrad, G. (TA)
;
Horel, E. (TA)
;
Li, Y. (TA)
;
Lyman, L. (TA)
CME 244: Project Course in Mathematical and Computational Finance
For graduate students in the MCF track; students will work individually or in groups on research projects.
Terms: Aut, Win, Spr, Sum

Units: 16

Grading: Letter (ABCD/NP)
Instructors:
Jain, K. (PI)
;
Horel, E. (TA)
CME 245: Topics in Mathematical and Computational Finance
Description: Current topics for enrolled students in the MCF program: This course is an introduction to computational, statistical, and optimizations methods and their application to financial markets. Class will consist of lectures and realtime problem solving. Topics: Python & R programming, interest rates, BlackScholes model, financial time series, capital asset pricing model (CAPM), options, optimization methods, and machine learning algorithms. Appropriate for anyone with a technical and solid applied math background interested in honing skills in quantitative finance. Prerequisite: basic statistics and exposure to programming.Can be repeated up to three times.
Terms: Aut, Win, Spr, Sum

Units: 1

Repeatable for credit

Grading: Satisfactory/No Credit
Instructors:
Jain, K. (PI)
;
Sircar, K. (PI)
CME 263: Introduction to Linear Dynamical Systems (EE 263)
Applied linear algebra and linear dynamical systems with applications to circuits, signal processing, communications, and control systems. Topics: leastsquares approximations of overdetermined equations, and leastnorm solutions of underdetermined equations. Symmetric matrices, matrix norm, and singularvalue decomposition. Eigenvalues, left and right eigenvectors, with dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multiinput/multioutput systems, impulse and step matrices; convolution and transfermatrix descriptions. Control, reachability, and state transfer; observability and leastsquares state estimation. Prerequisites: linear algebra and matrices as in
MATH104; differential equations and Laplace transforms as in
EE102B.
Terms: Aut, Sum

Units: 3

Grading: Letter or Credit/No Credit
Instructors:
Nasiri Mahalati, R. (PI)
;
Shah, K. (PI)
;
Bartan, B. (TA)
...
more instructors for CME 263 »
Instructors:
Nasiri Mahalati, R. (PI)
;
Shah, K. (PI)
;
Bartan, B. (TA)
;
Hemmati, S. (TA)
;
Momeni, A. (TA)
;
Shah, K. (TA)
;
Sharafat, A. (TA)
;
Shen, L. (TA)
;
Zhou, Z. (TA)
CME 291: Master's Research
Students require faculty sponsor. (Staff)
Terms: Aut, Win, Spr, Sum

Units: 16

Repeatable for credit

Grading: Letter or Credit/No Credit
Instructors:
Aiken, A. (PI)
;
Alonso, J. (PI)
;
Bambos, N. (PI)
;
Biondi, B. (PI)
;
Boneh, D. (PI)
;
Bosagh Zadeh, R. (PI)
;
Boyd, S. (PI)
;
Butte, A. (PI)
;
Candes, E. (PI)
;
Carlsson, G. (PI)
;
Constantinou, C. (PI)
;
Darve, E. (PI)
;
Davis, R. (PI)
;
Diaconis, P. (PI)
;
Donoho, D. (PI)
;
Farhat, C. (PI)
;
Fedkiw, R. (PI)
;
Feinstein, J. (PI)
;
Fringer, O. (PI)
;
Fruchter, R. (PI)
;
Gerritsen, M. (PI)
;
Giesecke, K. (PI)
;
Glynn, P. (PI)
;
Goel, A. (PI)
;
Guibas, L. (PI)
;
Hanrahan, P. (PI)
;
Harris, J. (PI)
;
Imbens, G. (PI)
;
Jain, K. (PI)
;
Jameson, A. (PI)
;
Johari, R. (PI)
;
Kahn, S. (PI)
;
Kamvar, S. (PI)
;
Khayms, V. (PI)
;
Koltun, V. (PI)
;
Langley, P. (PI)
;
Lele, S. (PI)
;
Leskovec, J. (PI)
;
Levinson, D. (PI)
;
Lew, A. (PI)
;
Liu, T. (PI)
;
Manning, C. (PI)
;
McFarland, D. (PI)
;
Mignot, E. (PI)
;
Moin, P. (PI)
;
Mummolo, J. (PI)
;
Murray, W. (PI)
;
Napel, S. (PI)
;
Ng, A. (PI)
;
Papanicolaou, G. (PI)
;
Pelger, M. (PI)
;
Rajaratnam, B. (PI)
;
Re, C. (PI)
;
Reed, E. (PI)
;
Saberi, A. (PI)
;
Saunders, M. (PI)
;
Schwartzman, A. (PI)
;
Shaqfeh, E. (PI)
;
Suckale, J. (PI)
;
Taylor, C. (PI)
;
Wall, D. (PI)
;
Wara, M. (PI)
;
Wechsler, R. (PI)
;
Weinstein, J. (PI)
;
Wong, W. (PI)
;
Ye, Y. (PI)
;
Zenios, S. (PI)
;
Zou, J. (PI)
CME 364A: Convex Optimization I (CS 334A, EE 364A)
Convex sets, functions, and optimization problems. The basics of convex analysis and theory of convex programming: optimality conditions, duality theory, theorems of alternative, and applications. Leastsquares, linear and quadratic programs, semidefinite programming, and geometric programming. Numerical algorithms for smooth and equality constrained problems; interiorpoint methods for inequality constrained problems. Applications to signal processing, communications, control, analog and digital circuit design, computational geometry, statistics, machine learning, and mechanical engineering. Prerequisite: linear algebra such as
EE263, basic probability.
Terms: Spr, Sum

Units: 3

Grading: Letter or Credit/No Credit
Instructors:
Angeris, G. (PI)
;
Boyd, S. (PI)
;
Momeni, A. (PI)
;
Agrawal, A. (TA)
;
Alexandari, A. (TA)
;
Fu, R. (TA)
;
Hemmati, S. (TA)
;
Lim, R. (TA)
;
Momeni, A. (TA)
;
Sharafat, A. (TA)
;
Sheng, H. (TA)
;
Sun, Q. (TA)
;
Yu, G. (TA)
;
Zaidi, M. (TA)
;
Zhang, J. (TA)
CME 390: Curricular Practical Training
Educational opportunities in high technology research and development labs in applied mathematics. Qualified ICME students engage in internship work and integrate that work into their academic program. Students register during the quarter they are employed and complete a research report outlining their work activity, problems investigated, results, and followon projects they expect to perform. May be repeated three times for credit.
Terms: Aut, Win, Spr, Sum

Units: 1

Repeatable for credit

Grading: Satisfactory/No Credit
CME 399: Special Research Topics in Computational and Mathematical Engineering
Graduatelevel research work not related to report, thesis, or dissertation. May be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 115

Repeatable for credit

Grading: Letter or Credit/No Credit
Instructors:
Boyd, S. (PI)
;
Candes, E. (PI)
;
Carlsson, G. (PI)
;
Darve, E. (PI)
;
Gerritsen, M. (PI)
;
Hastie, T. (PI)
;
Kamvar, S. (PI)
;
Levi, O. (PI)